Projekteja vuodessa
Abstrakti
We consider a parallelserver system with homogeneous servers where incoming tasks, arriving at rate λ, are dispatched by n dispatchers, each of them balancing a fraction 1/n of the load to K/n servers. Servers are firstcomefirstserved (FCFS) queues and dispatchers implement size interval task assignment policy with equal load (SITAE), a sizebased policy such that the servers are equally loaded. We compare the performance of a system with n>1 dispatchers and a single dispatcher. We show that the performance of a system with n dispatchers, K servers, and arrival rate λ coincides with that of a system with one dispatcher, K/n servers, and arrival rate λ/n. We define the degradation factor as the ratio between the performance of a system with K servers and arrival rate λ and the performance of a system with K/n servers and arrival rate λ/n. We establish a partial monotonicity on n for the degradation factor and, therefore, the degradation factor is lower bounded by one. We then investigate the upper bound of the degradation factor for particular distributions. We consider two continuous service time distributions: uniform and bounded Pareto and a discrete distribution with two values, which is the distribution that maximizes the variance for a given mean. We show that the performance degradation is small for uniformly distributed job sizes but that for Bounded Pareto and two points distributions it can be unbounded. We have investigated the degradation using the distribution obtained from real traces.
Alkuperäiskieli  Englanti 

Artikkeli  8672485 
Sivut  875  888 
Sivumäärä  14 
Julkaisu  IEEE/ACM Transactions on Networking 
Vuosikerta  27 
Numero  2 
Varhainen verkossa julkaisun päivämäärä  2019 
DOI  pysyväislinkit  
Tila  Julkaistu  1 huhtik. 2019 
OKMjulkaisutyyppi  A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä 
Sormenjälki
Sukella tutkimusaiheisiin 'Performance Degradation in ParallelServer Systems'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.Projektit
 1 Päättynyt

Faster Queues for Big Data  Nopeammat jonot suurten tietomassojen käsittelyyn
Hyytiä, E., Aalto, S., Viitasaari, L., Wu, X., Bilenne, O. & Osti, P.
01/01/2016 → 31/12/2017
Projekti: Academy of Finland: Other research funding